Prediksi Nilai Mata Uang Emas Terhadap US Dollar (XAUUSD) Menggunakan Metode Hibrida Gated Recurrent Unit - Long Short-Term Memor

• Rio Mahendra Denta Saputra
• 14220005

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ABSTRAK

Pasar Forex adalah pasar global untuk perdagangan mata uang. Pasar ini adalah yang terbesar dan paling likuid di dunia, dengan volume perdagangan harian yang mencapai triliunan dolar. Tujuan dari penelitian ini adalah untuk mengembangkan model prediktif yang akurat dalam meramalkan pergerakan harga emas terhadap dolar AS (XAUUSD) di pasar Forex. Penelitian ini mengintegrasikan teknik Data Mining dan analisis Time Series dengan algoritma deep learning, khususnya model hibrida GRU- LSTM. Data yang digunakan mencakup periode dari bulan Januari tahun 2021 hingga bulan Oktober tahun 2023, diperoleh dari investing.com. Data dievaluasi menggunakan dua set data yang dibagi dengan rasio data latih dan data uji sebesar 80:20 dan 85:15. Hasil penelitian menunjukkan bahwa model hibrida GRU-LSTM dengan epoch 50 serta lookback dan timestep sebesar 20 menghasilkan performa terbaik pada dataset dengan pembagian data 80:20 dengan RMSE 13.4908, MAE 9.8075, MAPE 0.5055, dan R² score 0.8964. Sedangkan performa terbaik pada dataset dengan pembagian data 85:15 diraih oleh model hibrida GRU-LSTM dengan epoch 100 serta lookback dan timestep sebesar 15 dengan RMSE 12.4676, MAE 8.8498, MAPE 0.4602, dan R² score 0.8923.

Kata kunci: Forex, Prediksi XAUUSD, GRU-LSTM, Time Series, Data Mining

KATA KUNCI

Forex,GRU-LSTM,Prediksi XAUUSD,Data Mining

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